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<FONT color="green">001</FONT>    /*<a name="line.1"></a>
<FONT color="green">002</FONT>     * Licensed to the Apache Software Foundation (ASF) under one or more<a name="line.2"></a>
<FONT color="green">003</FONT>     * contributor license agreements.  See the NOTICE file distributed with<a name="line.3"></a>
<FONT color="green">004</FONT>     * this work for additional information regarding copyright ownership.<a name="line.4"></a>
<FONT color="green">005</FONT>     * The ASF licenses this file to You under the Apache License, Version 2.0<a name="line.5"></a>
<FONT color="green">006</FONT>     * (the "License"); you may not use this file except in compliance with<a name="line.6"></a>
<FONT color="green">007</FONT>     * the License.  You may obtain a copy of the License at<a name="line.7"></a>
<FONT color="green">008</FONT>     *<a name="line.8"></a>
<FONT color="green">009</FONT>     *      http://www.apache.org/licenses/LICENSE-2.0<a name="line.9"></a>
<FONT color="green">010</FONT>     *<a name="line.10"></a>
<FONT color="green">011</FONT>     * Unless required by applicable law or agreed to in writing, software<a name="line.11"></a>
<FONT color="green">012</FONT>     * distributed under the License is distributed on an "AS IS" BASIS,<a name="line.12"></a>
<FONT color="green">013</FONT>     * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.<a name="line.13"></a>
<FONT color="green">014</FONT>     * See the License for the specific language governing permissions and<a name="line.14"></a>
<FONT color="green">015</FONT>     * limitations under the License.<a name="line.15"></a>
<FONT color="green">016</FONT>     */<a name="line.16"></a>
<FONT color="green">017</FONT>    package org.apache.commons.math.stat.regression;<a name="line.17"></a>
<FONT color="green">018</FONT>    <a name="line.18"></a>
<FONT color="green">019</FONT>    import org.apache.commons.math.MathRuntimeException;<a name="line.19"></a>
<FONT color="green">020</FONT>    import org.apache.commons.math.linear.RealMatrix;<a name="line.20"></a>
<FONT color="green">021</FONT>    import org.apache.commons.math.linear.Array2DRowRealMatrix;<a name="line.21"></a>
<FONT color="green">022</FONT>    import org.apache.commons.math.linear.RealVector;<a name="line.22"></a>
<FONT color="green">023</FONT>    import org.apache.commons.math.linear.ArrayRealVector;<a name="line.23"></a>
<FONT color="green">024</FONT>    <a name="line.24"></a>
<FONT color="green">025</FONT>    /**<a name="line.25"></a>
<FONT color="green">026</FONT>     * Abstract base class for implementations of MultipleLinearRegression.<a name="line.26"></a>
<FONT color="green">027</FONT>     * @version $Revision: 791244 $ $Date: 2009-07-05 09:29:37 -0400 (Sun, 05 Jul 2009) $<a name="line.27"></a>
<FONT color="green">028</FONT>     * @since 2.0<a name="line.28"></a>
<FONT color="green">029</FONT>     */<a name="line.29"></a>
<FONT color="green">030</FONT>    public abstract class AbstractMultipleLinearRegression implements<a name="line.30"></a>
<FONT color="green">031</FONT>            MultipleLinearRegression {<a name="line.31"></a>
<FONT color="green">032</FONT>    <a name="line.32"></a>
<FONT color="green">033</FONT>        /** X sample data. */<a name="line.33"></a>
<FONT color="green">034</FONT>        protected RealMatrix X;<a name="line.34"></a>
<FONT color="green">035</FONT>    <a name="line.35"></a>
<FONT color="green">036</FONT>        /** Y sample data. */<a name="line.36"></a>
<FONT color="green">037</FONT>        protected RealVector Y;<a name="line.37"></a>
<FONT color="green">038</FONT>    <a name="line.38"></a>
<FONT color="green">039</FONT>        /**<a name="line.39"></a>
<FONT color="green">040</FONT>         * Loads model x and y sample data from a flat array of data, overriding any previous sample.<a name="line.40"></a>
<FONT color="green">041</FONT>         * Assumes that rows are concatenated with y values first in each row.<a name="line.41"></a>
<FONT color="green">042</FONT>         * <a name="line.42"></a>
<FONT color="green">043</FONT>         * @param data input data array<a name="line.43"></a>
<FONT color="green">044</FONT>         * @param nobs number of observations (rows)<a name="line.44"></a>
<FONT color="green">045</FONT>         * @param nvars number of independent variables (columns, not counting y)<a name="line.45"></a>
<FONT color="green">046</FONT>         */<a name="line.46"></a>
<FONT color="green">047</FONT>        public void newSampleData(double[] data, int nobs, int nvars) {<a name="line.47"></a>
<FONT color="green">048</FONT>            double[] y = new double[nobs];<a name="line.48"></a>
<FONT color="green">049</FONT>            double[][] x = new double[nobs][nvars + 1];<a name="line.49"></a>
<FONT color="green">050</FONT>            int pointer = 0;<a name="line.50"></a>
<FONT color="green">051</FONT>            for (int i = 0; i &lt; nobs; i++) {<a name="line.51"></a>
<FONT color="green">052</FONT>                y[i] = data[pointer++];<a name="line.52"></a>
<FONT color="green">053</FONT>                x[i][0] = 1.0d;<a name="line.53"></a>
<FONT color="green">054</FONT>                for (int j = 1; j &lt; nvars + 1; j++) {<a name="line.54"></a>
<FONT color="green">055</FONT>                    x[i][j] = data[pointer++];<a name="line.55"></a>
<FONT color="green">056</FONT>                }<a name="line.56"></a>
<FONT color="green">057</FONT>            }<a name="line.57"></a>
<FONT color="green">058</FONT>            this.X = new Array2DRowRealMatrix(x);<a name="line.58"></a>
<FONT color="green">059</FONT>            this.Y = new ArrayRealVector(y);<a name="line.59"></a>
<FONT color="green">060</FONT>        }<a name="line.60"></a>
<FONT color="green">061</FONT>        <a name="line.61"></a>
<FONT color="green">062</FONT>        /**<a name="line.62"></a>
<FONT color="green">063</FONT>         * Loads new y sample data, overriding any previous sample<a name="line.63"></a>
<FONT color="green">064</FONT>         * <a name="line.64"></a>
<FONT color="green">065</FONT>         * @param y the [n,1] array representing the y sample<a name="line.65"></a>
<FONT color="green">066</FONT>         */<a name="line.66"></a>
<FONT color="green">067</FONT>        protected void newYSampleData(double[] y) {<a name="line.67"></a>
<FONT color="green">068</FONT>            this.Y = new ArrayRealVector(y);<a name="line.68"></a>
<FONT color="green">069</FONT>        }<a name="line.69"></a>
<FONT color="green">070</FONT>    <a name="line.70"></a>
<FONT color="green">071</FONT>        /**<a name="line.71"></a>
<FONT color="green">072</FONT>         * Loads new x sample data, overriding any previous sample<a name="line.72"></a>
<FONT color="green">073</FONT>         * <a name="line.73"></a>
<FONT color="green">074</FONT>         * @param x the [n,k] array representing the x sample<a name="line.74"></a>
<FONT color="green">075</FONT>         */<a name="line.75"></a>
<FONT color="green">076</FONT>        protected void newXSampleData(double[][] x) {<a name="line.76"></a>
<FONT color="green">077</FONT>            this.X = new Array2DRowRealMatrix(x);<a name="line.77"></a>
<FONT color="green">078</FONT>        }<a name="line.78"></a>
<FONT color="green">079</FONT>    <a name="line.79"></a>
<FONT color="green">080</FONT>        /**<a name="line.80"></a>
<FONT color="green">081</FONT>         * Validates sample data.<a name="line.81"></a>
<FONT color="green">082</FONT>         * <a name="line.82"></a>
<FONT color="green">083</FONT>         * @param x the [n,k] array representing the x sample<a name="line.83"></a>
<FONT color="green">084</FONT>         * @param y the [n,1] array representing the y sample<a name="line.84"></a>
<FONT color="green">085</FONT>         * @throws IllegalArgumentException if the x and y array data are not<a name="line.85"></a>
<FONT color="green">086</FONT>         *             compatible for the regression<a name="line.86"></a>
<FONT color="green">087</FONT>         */<a name="line.87"></a>
<FONT color="green">088</FONT>        protected void validateSampleData(double[][] x, double[] y) {<a name="line.88"></a>
<FONT color="green">089</FONT>            if ((x == null) || (y == null) || (x.length != y.length)) {<a name="line.89"></a>
<FONT color="green">090</FONT>                throw MathRuntimeException.createIllegalArgumentException(<a name="line.90"></a>
<FONT color="green">091</FONT>                      "dimension mismatch {0} != {1}",<a name="line.91"></a>
<FONT color="green">092</FONT>                      (x == null) ? 0 : x.length,<a name="line.92"></a>
<FONT color="green">093</FONT>                      (y == null) ? 0 : y.length);<a name="line.93"></a>
<FONT color="green">094</FONT>            } else if ((x.length &gt; 0) &amp;&amp; (x[0].length &gt; x.length)) {<a name="line.94"></a>
<FONT color="green">095</FONT>                throw MathRuntimeException.createIllegalArgumentException(<a name="line.95"></a>
<FONT color="green">096</FONT>                      "not enough data ({0} rows) for this many predictors ({1} predictors)",<a name="line.96"></a>
<FONT color="green">097</FONT>                      x.length, x[0].length);<a name="line.97"></a>
<FONT color="green">098</FONT>            }<a name="line.98"></a>
<FONT color="green">099</FONT>        }<a name="line.99"></a>
<FONT color="green">100</FONT>    <a name="line.100"></a>
<FONT color="green">101</FONT>        /**<a name="line.101"></a>
<FONT color="green">102</FONT>         * Validates sample data.<a name="line.102"></a>
<FONT color="green">103</FONT>         * <a name="line.103"></a>
<FONT color="green">104</FONT>         * @param x the [n,k] array representing the x sample<a name="line.104"></a>
<FONT color="green">105</FONT>         * @param covariance the [n,n] array representing the covariance matrix<a name="line.105"></a>
<FONT color="green">106</FONT>         * @throws IllegalArgumentException if the x sample data or covariance<a name="line.106"></a>
<FONT color="green">107</FONT>         *             matrix are not compatible for the regression<a name="line.107"></a>
<FONT color="green">108</FONT>         */<a name="line.108"></a>
<FONT color="green">109</FONT>        protected void validateCovarianceData(double[][] x, double[][] covariance) {<a name="line.109"></a>
<FONT color="green">110</FONT>            if (x.length != covariance.length) {<a name="line.110"></a>
<FONT color="green">111</FONT>                throw MathRuntimeException.createIllegalArgumentException(<a name="line.111"></a>
<FONT color="green">112</FONT>                     "dimension mismatch {0} != {1}", x.length, covariance.length);<a name="line.112"></a>
<FONT color="green">113</FONT>            }<a name="line.113"></a>
<FONT color="green">114</FONT>            if (covariance.length &gt; 0 &amp;&amp; covariance.length != covariance[0].length) {<a name="line.114"></a>
<FONT color="green">115</FONT>                throw MathRuntimeException.createIllegalArgumentException(<a name="line.115"></a>
<FONT color="green">116</FONT>                      "a {0}x{1} matrix was provided instead of a square matrix",<a name="line.116"></a>
<FONT color="green">117</FONT>                      covariance.length, covariance[0].length);<a name="line.117"></a>
<FONT color="green">118</FONT>            }<a name="line.118"></a>
<FONT color="green">119</FONT>        }<a name="line.119"></a>
<FONT color="green">120</FONT>    <a name="line.120"></a>
<FONT color="green">121</FONT>        /**<a name="line.121"></a>
<FONT color="green">122</FONT>         * {@inheritDoc}<a name="line.122"></a>
<FONT color="green">123</FONT>         */<a name="line.123"></a>
<FONT color="green">124</FONT>        public double[] estimateRegressionParameters() {<a name="line.124"></a>
<FONT color="green">125</FONT>            RealVector b = calculateBeta();<a name="line.125"></a>
<FONT color="green">126</FONT>            return b.getData();<a name="line.126"></a>
<FONT color="green">127</FONT>        }<a name="line.127"></a>
<FONT color="green">128</FONT>    <a name="line.128"></a>
<FONT color="green">129</FONT>        /**<a name="line.129"></a>
<FONT color="green">130</FONT>         * {@inheritDoc}<a name="line.130"></a>
<FONT color="green">131</FONT>         */<a name="line.131"></a>
<FONT color="green">132</FONT>        public double[] estimateResiduals() {<a name="line.132"></a>
<FONT color="green">133</FONT>            RealVector b = calculateBeta();<a name="line.133"></a>
<FONT color="green">134</FONT>            RealVector e = Y.subtract(X.operate(b));<a name="line.134"></a>
<FONT color="green">135</FONT>            return e.getData();<a name="line.135"></a>
<FONT color="green">136</FONT>        }<a name="line.136"></a>
<FONT color="green">137</FONT>    <a name="line.137"></a>
<FONT color="green">138</FONT>        /**<a name="line.138"></a>
<FONT color="green">139</FONT>         * {@inheritDoc}<a name="line.139"></a>
<FONT color="green">140</FONT>         */<a name="line.140"></a>
<FONT color="green">141</FONT>        public double[][] estimateRegressionParametersVariance() {<a name="line.141"></a>
<FONT color="green">142</FONT>            return calculateBetaVariance().getData();<a name="line.142"></a>
<FONT color="green">143</FONT>        }<a name="line.143"></a>
<FONT color="green">144</FONT>        <a name="line.144"></a>
<FONT color="green">145</FONT>        /**<a name="line.145"></a>
<FONT color="green">146</FONT>         * {@inheritDoc}<a name="line.146"></a>
<FONT color="green">147</FONT>         */<a name="line.147"></a>
<FONT color="green">148</FONT>        public double[] estimateRegressionParametersStandardErrors() {<a name="line.148"></a>
<FONT color="green">149</FONT>            double[][] betaVariance = estimateRegressionParametersVariance();<a name="line.149"></a>
<FONT color="green">150</FONT>            double sigma = calculateYVariance();<a name="line.150"></a>
<FONT color="green">151</FONT>            int length = betaVariance[0].length;<a name="line.151"></a>
<FONT color="green">152</FONT>            double[] result = new double[length];<a name="line.152"></a>
<FONT color="green">153</FONT>            for (int i = 0; i &lt; length; i++) {<a name="line.153"></a>
<FONT color="green">154</FONT>                result[i] = Math.sqrt(sigma * betaVariance[i][i]);<a name="line.154"></a>
<FONT color="green">155</FONT>            }<a name="line.155"></a>
<FONT color="green">156</FONT>            return result;<a name="line.156"></a>
<FONT color="green">157</FONT>        }<a name="line.157"></a>
<FONT color="green">158</FONT>    <a name="line.158"></a>
<FONT color="green">159</FONT>        /**<a name="line.159"></a>
<FONT color="green">160</FONT>         * {@inheritDoc}<a name="line.160"></a>
<FONT color="green">161</FONT>         */<a name="line.161"></a>
<FONT color="green">162</FONT>        public double estimateRegressandVariance() {<a name="line.162"></a>
<FONT color="green">163</FONT>            return calculateYVariance();<a name="line.163"></a>
<FONT color="green">164</FONT>        }<a name="line.164"></a>
<FONT color="green">165</FONT>    <a name="line.165"></a>
<FONT color="green">166</FONT>        /**<a name="line.166"></a>
<FONT color="green">167</FONT>         * Calculates the beta of multiple linear regression in matrix notation.<a name="line.167"></a>
<FONT color="green">168</FONT>         * <a name="line.168"></a>
<FONT color="green">169</FONT>         * @return beta<a name="line.169"></a>
<FONT color="green">170</FONT>         */<a name="line.170"></a>
<FONT color="green">171</FONT>        protected abstract RealVector calculateBeta();<a name="line.171"></a>
<FONT color="green">172</FONT>    <a name="line.172"></a>
<FONT color="green">173</FONT>        /**<a name="line.173"></a>
<FONT color="green">174</FONT>         * Calculates the beta variance of multiple linear regression in matrix<a name="line.174"></a>
<FONT color="green">175</FONT>         * notation.<a name="line.175"></a>
<FONT color="green">176</FONT>         * <a name="line.176"></a>
<FONT color="green">177</FONT>         * @return beta variance<a name="line.177"></a>
<FONT color="green">178</FONT>         */<a name="line.178"></a>
<FONT color="green">179</FONT>        protected abstract RealMatrix calculateBetaVariance();<a name="line.179"></a>
<FONT color="green">180</FONT>    <a name="line.180"></a>
<FONT color="green">181</FONT>        /**<a name="line.181"></a>
<FONT color="green">182</FONT>         * Calculates the Y variance of multiple linear regression.<a name="line.182"></a>
<FONT color="green">183</FONT>         * <a name="line.183"></a>
<FONT color="green">184</FONT>         * @return Y variance<a name="line.184"></a>
<FONT color="green">185</FONT>         */<a name="line.185"></a>
<FONT color="green">186</FONT>        protected abstract double calculateYVariance();<a name="line.186"></a>
<FONT color="green">187</FONT>    <a name="line.187"></a>
<FONT color="green">188</FONT>        /**<a name="line.188"></a>
<FONT color="green">189</FONT>         * Calculates the residuals of multiple linear regression in matrix<a name="line.189"></a>
<FONT color="green">190</FONT>         * notation.<a name="line.190"></a>
<FONT color="green">191</FONT>         * <a name="line.191"></a>
<FONT color="green">192</FONT>         * &lt;pre&gt;<a name="line.192"></a>
<FONT color="green">193</FONT>         * u = y - X * b<a name="line.193"></a>
<FONT color="green">194</FONT>         * &lt;/pre&gt;<a name="line.194"></a>
<FONT color="green">195</FONT>         * <a name="line.195"></a>
<FONT color="green">196</FONT>         * @return The residuals [n,1] matrix<a name="line.196"></a>
<FONT color="green">197</FONT>         */<a name="line.197"></a>
<FONT color="green">198</FONT>        protected RealVector calculateResiduals() {<a name="line.198"></a>
<FONT color="green">199</FONT>            RealVector b = calculateBeta();<a name="line.199"></a>
<FONT color="green">200</FONT>            return Y.subtract(X.operate(b));<a name="line.200"></a>
<FONT color="green">201</FONT>        }<a name="line.201"></a>
<FONT color="green">202</FONT>    <a name="line.202"></a>
<FONT color="green">203</FONT>    }<a name="line.203"></a>




























































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